Sight Machine introduces crews of autonomous AI agents that work around the clock to optimize manufacturing performance using its industrial AI platform and semantic layer. The agentic operations, demonstrated at Hannover Messe 2026, accelerate AI outcomes in production by solving complex problems in throughput, quality, and cost while maintaining human oversight.
Quick Intel
Sight Machine Inc., the leading industrial AI platform, today introduced autonomous agentic operations in manufacturing, with crews of autonomous AI agents working around the clock to maximize production performance. These capabilities, which Sight Machine is demonstrating this week at the trade fair Hannover Messe, dramatically accelerate the timeline for manufacturers to achieve outcomes using AI.
General-purpose AI tools are unable to make sense of raw industrial data. Sight Machine's crews of AI agents solve production problems and improve productivity by working with Sight Machine's semantic layer, a continuously updated digital representation of manufacturing processes generated by Sight Machine's industrial AI platform.
While individual agents focus on improving KPIs like throughput, quality, and cost, they work together as a crew to achieve overall optimization of manufacturing and business outcomes. Agents use Sight Machine's extensive set of manufacturing analysis tools, and work with developer agents to create custom analysis applications when needed, within guardrails.
Sight Machine is also building the capacity of its agents to deploy its industrial data platform and configure the semantic layer, accelerating implementations and putting operations teams in control. By using agents, operating teams are empowered to extend the semantic layer to include new machines, lines, and product SKUs. This reduces reliance on software developers and specialist systems integrators and puts more power and flexibility into the hands of users.
"By melding the rapidly advancing power of AI technologies with the unique semantic layer generated by Sight Machine's industrial AI platform, Sight Machine has bridged the gap between general-purpose AI technology and the extremely challenging nature of production data," said Sight Machine CEO and Co-Founder Jon Sobel. "Sight Machine is the linchpin enabling AI to work effectively in the physical world of manufacturing."
Advancing Toward Autonomous Operations The AI agent crew initially operates in analysis and recommendation mode to simulate possibilities, determine optimal settings, and make recommendations to operations teams. As the agentic crew demonstrates its capabilities and reliability, manufacturers can choose to extend its authority to directly control specific settings or steps – moving progressively toward autonomous operations at a pace they control.
The agent crews use Sight Machine's manufacturing analytics tools, including statistical analysis, ML techniques (e.g., random forest), AI-enhanced centerlining and golden runs, cookbooks, and root cause analytics. Within a permissioned framework that manufacturers control, the agent crew has the ability to code and orchestrate new tools for analysis, optimization and presentation.
The agents communicate with other agents and tools using Model Context Protocol (MCP), an open standard that enables secure, structured interoperability between AI agents and the tools they use. In addition to layers of security within Sight Machine's platform, the software runs within corporate security and data governance provided by Microsoft Azure.
"Operations teams assign objectives to agents, and each agent works continuously to achieve its objective, whether it is improving availability, minimizing defects, or maximizing throughput," said Sight Machine VP of Product Andrew Home. "The agents are always on, looking at current operating conditions, looking at all the process parameters, looking for anomalies and changes in conditions, and providing recommendations to operators on how they can improve."
Working under instructions provided by human operators, and with quality and conformance review by those operators, the crew of agents work together to balance tradeoffs among outcomes, e.g., maximizing throughput vs. quality. They can provide recommendations to optimize changeovers in the type of product being made or the raw materials used, such as changes to machine settings, temperature, process duration, etc.
Engaging with Operations Teams Through Productivity Tools Users can engage with and share the insights, recommendations and analysis of Sight Machine's industrial AI platform using ubiquitous productivity tools – including Microsoft Excel and Microsoft Teams – and through enterprise data platforms such as Microsoft Fabric and Databricks, rather than requiring specialist knowledge of manufacturing software.
Sight Machine is demonstrating agentic operations in Microsoft's booth (Hall 17, Stand G06) at Hannover Messe this week. The demonstration runs on the Sight Machine and Microsoft Integrated Industrial AI Stack on Azure, a fully integrated industrial AI solution jointly delivered by Microsoft and Sight Machine. This offering brings together the entire industrial AI stack spanning cloud, edge, and on-premises, enabling organizations to unlock transformative business value.
About Sight Machine
Sight Machine, the leading industrial AI platform, enables manufacturers to scale industrial AI across products, lines, and plants. Purpose-built for manufacturing and combining software with forward-deployed manufacturing experts, Sight Machine helps enterprises drive measurable improvements in yield, throughput, quality, uptime, cost, and sustainability. The platform is open, modular, and enterprise-grade, integrating natively into existing architectures while preserving full customer control of data and infrastructure.
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